Spatial Interpolation of Monthly and Annual Climate Variables in Jordan, (Wadi Al-Wala) Case Study

Authors : Rasheed. A. Shyyab; Seyedeh Hamideh Ebrahimi; Xinhai Lu

Volume/Issue : Volume 8 - 2023, Issue 8 - August

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The goal of this research was to assess and compare the differences in climate variables, specifically precipitation (rainfall) and temperature maps, which are crucial for many hydrological models. We utilized ordinary kriging and multivariate interpolation techniques to create maps of monthly and annual rainfall in the Wadi Al-wala region of Jordan. This involved collecting climate data from four rainfall stations (Al-Muwaqqar, Jiza, Dhaba' Nursery, Muleih) and the Er-Rabba metrological temperature station between 1980 and 2012. The patterns of spatial variation in the collected climate data were analyzed using geostatistical methods to identify spatial variances and predict the potential impacts of climate change on the Wadi Al-Wala region. An experimental variogram of the data was created and compared against three common geostatistical models. Then spatial maps of the climate variables were prepared through the kriging technique by using the best-fit geostatistical model, which help choose appropriate values of model parameters. Nugget- to-sill ratio (<0.25) revealed that the surface water levels have strong spatial dependence in the area. The statistical indicators (RSS and r2) suggested that any of the three geostatistical models, i.e., spherical, linear, and exponential, can be selected as the best-fit model for reliable and accurate spatial interpolation. However, exponential and spherical models were used as the best- fit models for the Al-Muwaqqar rainfall station with the lower residual sum of squares (RSS= 1.038) and high value of regression coefficient (r2= 0.192), and average mean temperature from Er-Rabba station with higher r2= 0.703 and RSS= 0.116 respectively, in the present study.

Keywords : Climate Variables, Wadi Al-Wala, Geostatics, Kriging Interpolation, Semivariance Analysis.


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31 - December - 2023

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